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--- |
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license: mit |
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--- |
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github: https://github.com/chongzicbo/MathImg2Latex/tree/main |
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``` |
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import torch |
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from PIL import Image |
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from transformers import VisionEncoderDecoderModel |
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from transformers.models.nougat import NougatTokenizerFast |
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from nougat_latex.util import process_raw_latex_code |
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from nougat_latex import NougatLaTexProcessor |
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os.environ["RUN_ON_GPU_IDs"] = "1" |
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device = torch.device("cpu") |
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model_path = "chongzicbo/MathImg2Latex" |
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tokenizer = NougatTokenizerFast.from_pretrained(model_path) |
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latex_processor = NougatLaTexProcessor.from_pretrained(model_path) |
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model = VisionEncoderDecoderModel.from_pretrained(model_path) |
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model.to(device) |
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img_path = "/data/code/MathOCR/MathImg2Latex/examples/test_data/test86_screenshot_bigger.jpg" |
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image = Image.open(img_path) |
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if not image.mode == "RGB": |
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image = image.convert("RGB") |
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pixel_values = latex_processor(image, return_tensors="pt").pixel_values |
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task_prompt = tokenizer.bos_token |
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decoder_input_ids = tokenizer( |
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task_prompt, add_special_tokens=False, return_tensors="pt" |
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).input_ids |
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with torch.no_grad(): |
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outputs = model.generate( |
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pixel_values.to(device), |
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decoder_input_ids=decoder_input_ids.to(device), |
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max_length=model.decoder.config.max_length, |
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early_stopping=True, |
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pad_token_id=tokenizer.pad_token_id, |
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eos_token_id=tokenizer.eos_token_id, |
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use_cache=True, |
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num_beams=1, |
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bad_words_ids=[[tokenizer.unk_token_id]], |
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return_dict_in_generate=True, |
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) |
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sequence = tokenizer.batch_decode(outputs.sequences)[0] |
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sequence = ( |
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sequence.replace(tokenizer.eos_token, "") |
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.replace(tokenizer.pad_token, "") |
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.replace(tokenizer.bos_token, "") |
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) |
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sequence = process_raw_latex_code(sequence) |
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print(sequence) |
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``` |
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